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Creating samples from a well-specified population (human: all adults; registered voters; individuals with diabetes; students of a university; establishment: all firms; firms with employment of 200 or more in New York City; resource: all land of a country or a state/province) using a probabilistic method, with the purpose of inference to that specific population
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Sampling without replacement
In the context of statistical inference and machine learning, bootstrapping is used to indicate sampling with replacement (e.g. in the context of Random Forest or calculating population standard devia …